Sergey Levine

Sergey Levine

Sergey Levine received a BS and MS in Computer Science from Stanford University in 2009, and a Ph.D. in Computer Science from Stanford University in 2014. He joined the faculty of the Department of Electrical Engineering and Computer Sciences at UC Berkeley in fall 2016. His work focuses on machine learning for decision making and control, with an emphasis on deep learning and reinforcement learning algorithms. Applications of his work include autonomous robots and vehicles, as well as applications in other decision-making domains. His research includes developing algorithms for end-to-end training of deep neural network policies that combine perception and control, scalable algorithms for inverse reinforcement learning, deep reinforcement learning algorithms, and more.

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  • Organization
    UC Berkeley
  • Profession
    Associate Professor
Related sessions
Discovery - AI and Robotics
Online
14 October 2025
18:00 - 19:00
EST - New York
CST - Beijing
PST - Los Angeles
AWST - Perth, Australia
In this talk, I will discuss how large neural network...

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